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35 Results

Poster
Mon 9:00 Effective Distributed Learning with Random Features: Improved Bounds and Algorithms
Yong Liu, Jiankun Liu, Shuqiang Wang
Spotlight
Mon 12:05 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Spotlight
Mon 12:15 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Poster
Mon 17:00 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Oral
Mon 21:21 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Poster
Tue 1:00 Large-width functional asymptotics for deep Gaussian neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
Poster
Tue 9:00 Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks
Christian Ali Mehmeti-Göpel, David Hartmann, Michael Wand
Poster
Tue 9:00 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, vladimir braverman, Quanquan Gu
Poster
Tue 9:00 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States
Dipendra Misra, Qinghua Liu, Chi Jin, John Langford
Poster
Tue 9:00 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Tue 9:00 Distance-Based Regularisation of Deep Networks for Fine-Tuning
Henry Gouk, Timothy Hospedales, massimiliano pontil
Poster
Tue 17:00 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Poster
Tue 17:00 A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, evren korpeoglu, Sushant Kumar, kannan achan
Poster
Tue 17:00 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen, Simran Kaur, Yuanzhi Li, Zico Kolter, Ameet Talwalkar
Poster
Tue 17:00 How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Du, Ken-Ichi Kawarabayashi, Stefanie Jegelka
Oral
Tue 19:55 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Poster
Wed 1:00 Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
Yu Cheng, Honghao Lin
Poster
Wed 9:00 For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal, Gal Kaplun, Boaz Barak
Poster
Wed 9:00 Theoretical bounds on estimation error for meta-learning
James Lucas, Mengye Ren, Irene Raissa KAMENI KAMENI, Toniann Pitassi, Richard Zemel
Poster
Wed 9:00 TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks
Martin Trimmel, Henning Petzka, Cristian Sminchisescu
Poster
Wed 17:00 In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
Poster
Wed 17:00 Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL
Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang
Spotlight
Wed 20:20 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Poster
Thu 9:00 Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee
Poster
Thu 9:00 Implicit Gradient Regularization
David Barrett, Benoit Dherin
Poster
Thu 17:00 Few-Shot Learning via Learning the Representation, Provably
Simon Du, Wei Hu, Sham M Kakade, Jason Lee, Qi Lei
Poster
Thu 17:00 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Poster
Thu 17:00 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Poster
Thu 17:00 A Learning Theoretic Perspective on Local Explainability
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar
Poster
Thu 17:00 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Oral
Thu 19:00 Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
Workshop
Fri 7:10 Invited Speaker Dan Roth - Natural Language Understanding with Incidental Supervision
Dan Roth
Workshop
Fri 12:15 A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via f-Divergences
Lalitha Sankar
Workshop
Fri 14:02 Invited Talk: A deep learning theory for neural networks grounded in physics
Benjamin Scellier